Staff Software Engineer

The Role

You'll join Digible's Engineering team as a senior individual contributor who ships meaningful product work while helping evolve how our teams build software. You may embed in key initiatives or pods and ship meaningful product features using advanced engineering practices.

• Think product-first by owning outcomes, not just tickets, and ensuring your work delivers real customer impact.
• Design, build, and ship features end-to-end, from problem definition through production.
• Use AI as a core part of your workflow, including writing specs, generating code, critically evaluating outputs, and improving development loops.
• Practice and model augmented coding while maintaining high standards for code quality, testing, system design, and deployment confidence.
• Pair with engineers inside their actual workflows to transfer practices through collaboration, not instruction.
• Drive ambiguous or high-impact problems when the path forward is unclear.
• Make thoughtful technical decisions with incomplete information and adjust when data or production reality points to a better path.
• Contribute across the full stack, including Node, TypeScript, React, SQL, and cloud-native services across AWS and GCP.
• Shape the technical foundation alongside feature work, including service boundaries, data flows, APIs, observability, reliability, and deployment practices.
• Debug complex issues across distributed systems and make architectural decisions that hold up beyond a single feature.
• Owning production systems, including observability, reliability, deployments, postmortems, and on-call responsibilities.
• Improve and evolve large, interconnected production codebases with empathy for legacy systems and the teams that maintain them.
• Influence technical direction within your pod and contribute to broader engineering improvements across pods.
• Leave systems, practices, and teams better than you found them.

  What You'll Do

  Embed in key initiatives or pods and ship meaningful product features using advanced engineering practices.

  • Think product-first by owning outcomes, not just tickets, and ensuring your work delivers real customer impact.
  • Design, build, and ship features end-to-end, from problem definition through production.
  • Use AI as a core part of your workflow, including writing specs, generating code, critically evaluating outputs, and improving development loops.
  • Practice and model augmented coding while maintaining high standards for code quality, testing, system design, and deployment confidence.
  • Pair with engineers inside their actual workflows to transfer practices through collaboration, not instruction.
  • Drive ambiguous or high-impact problems when the path forward is unclear.
  • Make thoughtful technical decisions with incomplete information and adjust when data or production reality points to a better path.
  • Contribute across the full stack, including Node, TypeScript, React, SQL, and cloud-native services across AWS and GCP.
  • Shape the technical foundation alongside feature work, including service boundaries, data flows, APIs, observability, reliability, and deployment practices.
  • Debug complex issues across distributed systems and make architectural decisions that hold up beyond a single feature.
  • Owning production systems, including observability, reliability, deployments, postmortems, and on-call responsibilities.
  • Improve and evolve large, interconnected production codebases with empathy for legacy systems and the teams that maintain them.
  • Influence technical direction within your pod and contribute to broader engineering improvements across pods.
  • Leave systems, practices, and teams better than you found them.